scBFA
This is the development version of scBFA; for the stable release version, see scBFA.
A dimensionality reduction tool using gene detection pattern to mitigate noisy expression profile of scRNA-seq
Bioconductor version: Development (3.20)
This package is designed to model gene detection pattern of scRNA-seq through a binary factor analysis model. This model allows user to pass into a cell level covariate matrix X and gene level covariate matrix Q to account for nuisance variance(e.g batch effect), and it will output a low dimensional embedding matrix for downstream analysis.
Author: Ruoxin Li [aut, cre], Gerald Quon [aut]
Maintainer: Ruoxin Li <uskli at ucdavis.edu>
citation("scBFA")
):
Installation
To install this package, start R (version "4.4") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
# The following initializes usage of Bioc devel
BiocManager::install(version='devel')
BiocManager::install("scBFA")
For older versions of R, please refer to the appropriate Bioconductor release.
Documentation
To view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("scBFA")
Gene Detection Analysis for scRNA-seq | HTML | R Script |
Reference Manual | ||
NEWS | Text | |
LICENSE | Text |
Details
biocViews | ATACSeq, BatchEffect, DimensionReduction, GeneExpression, KEGG, QualityControl, SingleCell, Software, Transcriptomics |
Version | 1.19.0 |
In Bioconductor since | BioC 3.10 (R-3.6) (5 years) |
License | GPL-3 + file LICENSE |
Depends | R (>= 3.6) |
Imports | SingleCellExperiment, SummarizedExperiment, Seurat, MASS, zinbwave, stats, copula, ggplot2, DESeq2, utils, grid, methods, Matrix |
System Requirements | |
URL | https://github.com/ucdavis/quon-titative-biology/BFA |
Bug Reports | https://github.com/ucdavis/quon-titative-biology/BFA/issues |
See More
Suggests | knitr, rmarkdown, testthat, Rtsne |
Linking To | |
Enhances | |
Depends On Me | |
Imports Me | |
Suggests Me | |
Links To Me | |
Build Report | Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
Source Package | scBFA_1.19.0.tar.gz |
Windows Binary | scBFA_1.19.0.zip |
macOS Binary (x86_64) | scBFA_1.19.0.tgz |
macOS Binary (arm64) | scBFA_1.19.0.tgz |
Source Repository | git clone https://git.bioconductor.org/packages/scBFA |
Source Repository (Developer Access) | git clone git@git.bioconductor.org:packages/scBFA |
Bioc Package Browser | https://code.bioconductor.org/browse/scBFA/ |
Package Short Url | https://bioconductor.org/packages/scBFA/ |
Package Downloads Report | Download Stats |